Updates on Auditory Outcomes of COVID-19 and Vaccine Side Effects: An Umbrella Review
Bibliographic record
Abstract
Purpose: This umbrella review synthesizes and discusses systematic reviews (SRs) and meta-analyses (MAs) on auditory outcomes associated with COVID-19 infection and vaccination side effects. It is innovative in offering a comprehensive synthesis of evidence across adults and infants while summarizing vaccine-related auditory side effects. Method: This literature search followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines, with no restrictions on population age or symptom severity. Four electronic databases were searched from their inception to October 2024. The Assessment of Multiple Systematic Reviews 2 checklist and Risk of Bias in Systematic Reviews tool were used to assess the quality of evidence and the risk of bias. Results: The systematic search identified 534 articles, narrowed down to 14 SRs following a full-text review: Nine focused on auditory outcomes of COVID-19; two, on outcomes in infants born to mothers infected during pregnancy; and three, on the auditory side effects of vaccination. A random-effects model revealed significantly high pooled estimates of hearing loss (5.0%, 95% CI [1.0, 9.0], p < .012, three MAs, N = 21,932) and tinnitus (13.5%, 95% CI [5.9, 21.1], p ≤ .001, four MAs, N = 36,236) in adults. However, current evidence in nonhospitalized patients indicates that auditory symptoms often improve after recovery. Studies also show a low rate of hearing loss in infants whose mothers contracted COVID-19 during pregnancy. Similarly, whereas COVID-19 vaccination has been linked to hearing loss and tinnitus, these effects are rare, and most patients experience improvement within weeks to months. Conclusions: Evidence suggests a significantly high rate of hearing loss and tinnitus associated with COVID-19 in adults, although auditory symptoms remain rare in newborns and following vaccination. However, caution is warranted due to limitations and variability across the studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".